Data analytics for operations management in a selected outsourced semiconductor assembly and test (OSAT) manufacturing company

College

College of Computer Studies

Department/Unit

Computer Science

Document Type

Conference Proceeding

Source Title

DLSU Research Congress 2021

First Page

1

Last Page

6

Publication Date

7-7-2021

Abstract

Encouraged by the increasing accessibility of data and recent advances in modern manufacturing and optimization methodologies, data analytics has been increasingly applied to operations management issues. If production processes become more complex and automated, the exploration of new operational insights must be automated. An OSAT manufacturing company's current methodology of assessing operational output (extracting and collecting data, running internal business models, producing reports, etc.) is primarily performed in a manual scheme. These manual tasks are time-consuming, inefficient, costly, and affect certain planning and organizational decisions, mistakes, or misjudgments. In this paper, the proponents initiated a project where a system was proposed and built using SDLC methodology to apply data analytics to operations management in three major areas – Shipment management, WIP management, and Output management. The project aims to automate the aggregation and evaluation of manufacturing data collected during operations in an OSAT manufacturing company by a manufacturing execution system (MES) and computer integrated manufacturing (CIM) system and to develop a data analytics system to support the analysis of operations results. The promoters concluded the paper by suggesting potential research areas.

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Disciplines

Computer Sciences | Data Science

Keywords

Production management—Data processing

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